“…According to Granić and Marangunić [9], 83 percent of research out of 71 relevant studies from 2003 to 2018 was subject to students' adoption behavior, whereas only 6 percent consisted of technology acceptance from the viewpoint of faculty. Out of a relatively small amount of work that investigated the difference between faculty and students in using technology in their teaching and learning, some researchers have reported that there are no significant differences between these two groups [16,46]. On the other hand, several researchers have provided empirical evidence that indicates noticeable differences between faculty and students.…”
Section: The Moderating Role Of User Typementioning
confidence: 99%
“…Existing studies pertaining to technology acceptance behavior in higher education are mostly posited from the standpoint of only the faculty [3,4] or are focused on just the student's perspective [7]. There are only a handful of studies [16,17] that investigate the difference between faculty and students regarding the development of behavioral intent toward technology-powered services for lecturing/learning purposes. Meanwhile, in the wake of COVID-19, there is a large body of study that addresses future outlooks of education in conjunction with technical solutions [18,19].…”
During the COVID-19 pandemic, learning management systems have become the primary channel for lecturing and learning in higher education contexts. The present study investigates the development of user acceptance behavior toward a learning management system through use of the extended technology acceptance model. Moreover, this research identified differences between faculty and student behavior in a university environment. Based on a quantitative approach, the analysis results revealed that the main triggers of user acceptance behavior are self-efficacy, enjoyment, and computer anxiety. This study also documented the different influencing factors between faculty members and student groups, respectively. This work is expected to add to existing knowledge and help guide those working in higher education settings to establish more effective strategies for the optimization of learning management systems.
“…According to Granić and Marangunić [9], 83 percent of research out of 71 relevant studies from 2003 to 2018 was subject to students' adoption behavior, whereas only 6 percent consisted of technology acceptance from the viewpoint of faculty. Out of a relatively small amount of work that investigated the difference between faculty and students in using technology in their teaching and learning, some researchers have reported that there are no significant differences between these two groups [16,46]. On the other hand, several researchers have provided empirical evidence that indicates noticeable differences between faculty and students.…”
Section: The Moderating Role Of User Typementioning
confidence: 99%
“…Existing studies pertaining to technology acceptance behavior in higher education are mostly posited from the standpoint of only the faculty [3,4] or are focused on just the student's perspective [7]. There are only a handful of studies [16,17] that investigate the difference between faculty and students regarding the development of behavioral intent toward technology-powered services for lecturing/learning purposes. Meanwhile, in the wake of COVID-19, there is a large body of study that addresses future outlooks of education in conjunction with technical solutions [18,19].…”
During the COVID-19 pandemic, learning management systems have become the primary channel for lecturing and learning in higher education contexts. The present study investigates the development of user acceptance behavior toward a learning management system through use of the extended technology acceptance model. Moreover, this research identified differences between faculty and student behavior in a university environment. Based on a quantitative approach, the analysis results revealed that the main triggers of user acceptance behavior are self-efficacy, enjoyment, and computer anxiety. This study also documented the different influencing factors between faculty members and student groups, respectively. This work is expected to add to existing knowledge and help guide those working in higher education settings to establish more effective strategies for the optimization of learning management systems.
This article explored the use of digital storytelling as a method to support multicultural counseling competency. Thematic analysis examined the experiences of 9 students who created a digital story through an immersion activity in a multicultural counseling course. Qualitative data revealed 4 themes: (a) initial discomfort with technology, (b) initial reservations with group work, (c) digital storytelling as a learning tool, and (d) multicultural counseling competency. Recommendations for counselor education and future research are provided.Este artículo exploró el uso de la narrativa digital como método para apoyar la competencia en consejería multicultural. Un análisis temático examinó las experiencias de 9 estudiantes que crearon una historia digital mediante una actividad de inmersión en un curso de consejería multicultural. Los datos cualitativos revelaron 4 temas: (a) una carencia inicial de familiaridad con la tecnología, (b) reservas iniciales en cuanto al trabajo en equipo, (c) la narrativa digital como herramienta de aprendizaje y (d) la competencia en consejería multicultural. Se ofrecen recomendaciones para la educación de consejeros e investigaciones futuras.
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